Novel Software Effort Estimation Method using Naive Bayes Technique

Predict the effort needed to make the product with help of support vector machine and manipulating prediction accuracy with Naive Bayes. Support Vector Machine with sample size =20 and Naive Bayes with sample size =20 was iterated for predicting the accuracy with a Pre-power test about 80%. In Software effort Calculation the result value ofSupport Vector Machine and Naive Bayesis 84.37% and 73.23%. The statistical comparision in accuracy of two algorithms is 0.002 (p<0.05, 2-tailed) from samples tests. The Support Vector Machine got the result significantly have improvement than Naive Bayes in calculating the effor estimation.